Lead Insurance Domain Architect
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Your day at NTT DATA
The Lead Insurance Domain Architect is a senior, client-facing domain leadership role responsible for translating insurance business needs into clear, actionable solution requirements and ensuring that technology solutions remain aligned with insurance processes, products, regulations, and business outcomes.
The role acts as the primary bridge between Insurance Domain stakeholders, Product Owners, Technology Architecture, AI/Data Science, Engineering, and Validation teams. The Domain Architect plays a central role in converting prototypes and business concepts into specifications, supporting backlog refinement, guiding builders, and ensuring that delivered solutions are validated against business intent.
The ideal candidate combines deep insurance industry expertise with strong solution-shaping capabilities and an understanding of AI-led, specification-driven development, where AI-assisted engineering tools accelerate the journey from business intent and specifications through implementation and validation.
Key Responsibilities
Insurance Domain Architecture & Solution Shaping
- Serve as the domain authority for insurance business capabilities, processes, products, data, and operating models.
- Translate business objectives and insurance use cases into domain architecture, business specifications, functional requirements, and acceptance criteria.
- Define the business context and domain boundaries required for technology and AI-enabled solutions.
- Ensure proposed solutions align with insurance industry practices, regulatory requirements, enterprise standards, and target business outcomes.
- Identify dependencies and impacts across the insurance value chain, including upstream and downstream processes and systems.
AI-Led, Specification-Driven Development
- Understand and actively participate in an AI-led, specification-driven development process, where well-defined specifications become the foundation for AI-assisted solution development.
- Translate business intent into precise, structured, and implementation-ready specifications that can be effectively consumed by both engineering teams and AI-assisted development tools.
- Work iteratively with Product Owners, Architects, and Builders to refine specifications based on generated solutions, prototypes, test results, and business feedback.
- Understand how AI coding assistants and agentic development tools can accelerate prototyping, code generation, testing, documentation, and solution refinement.
- Be familiar with modern AI-assisted development environments and tools such as GitHub-based development workspaces/tools, GitHub Copilot, Claude Code,...